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We derive global estimates for the error in solutions of linear hyperbolic systems due to inaccurate boundary geometry. We show that the error is bounded by data and bounded in time when the solutions in the true and approximate domains are…

Numerical Analysis · Mathematics 2025-03-27 David A. Kopriva , Andrew R. Winters , Jan Nordström

We study a distributed Kalman filtering problem in which a number of nodes cooperate without central coordination to estimate a common state based on local measurements and data received from neighbors. This is typically done by running a…

Systems and Control · Electrical Eng. & Systems 2021-02-18 Damián Marelli , Tianju Sui , Minyue Fu

We propose and analyze a posteriori error estimates for a control-constrained optimal control problem with bang-bang solutions. We consider a solution strategy based on the variational approach, where the control variable is not…

Optimization and Control · Mathematics 2025-05-26 Francisco Fuica

The convergence of a family of AMF-Runge-Kutta methods (in short AMF-RK) for the time integration of evolutionary Partial Differential Equations (PDEs) of Advection Diffusion Reaction type semi-discretized in space is considered. The…

Numerical Analysis · Mathematics 2015-01-13 Severiano Gonzalez Pinto , Domingo Hernandez Abreu , Soledad Perez Rodriguez

Local grid refinement aims to optimise the relationship between accuracy of the results and number of grid nodes. In the context of the finite volume method no single local refinement criterion has been globally established as optimum for…

Computational Physics · Physics 2015-08-11 Alexandros Syrakos , Georgios Efthimiou , John G. Bartzis , Apostolos Goulas

Correcting errors is a vital but expensive component of fault tolerant quantum computation. Standard fault tolerant protocol assumes the implementation of error correction, via syndrome measurements and possible recovery operations, after…

Quantum Physics · Physics 2013-08-09 Yaakov S. Weinstein

Interpolation-based methods are well-established and effective approaches for the efficient generation of accurate reduced-order surrogate models. Common challenges for such methods are the automatic selection of good or even optimal…

Numerical Analysis · Mathematics 2024-07-23 Quirin Aumann , Steffen W. R. Werner

We study the possibility of preventing finite-time disentanglement caused by dissipation by making use of "non-local quantum error correction. This is made in comparison of previous results, where was shown that "local" quantum error…

Quantum Physics · Physics 2008-06-13 Isabel Sainz , Gunnar Bjork

We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of (non-necessarily Hamiltonian) ordinary differential equations by means of Newton-like iterations. We pay particular…

Numerical Analysis · Mathematics 2017-03-23 Mikel Antoñana , Joseba Makazaga , Ander Murua

Achieving error rates that meet or exceed the fault-tolerance threshold is a central goal for quantum computing experiments, and measuring these error rates using randomized benchmarking is now routine. However, direct comparison between…

Quantum Physics · Physics 2016-10-26 Richard Kueng , David M. Long , Andrew C. Doherty , Steven T. Flammia

We study the construction and convergence of semi-explicit and iterative decoupling schemes for an elliptic-parabolic problem using higher-order Runge-Kutta methods. For the semi-explicit schemes, which are constructed using a nearby delay…

Numerical Analysis · Mathematics 2026-05-22 Robert Altmann , Abdullah Mujahid , Benjamin Unger

This paper introduces a generalization of the well-known Riccati recursion for solving the discrete-time equality-constrained linear quadratic optimal control problem. The recursion can be used to compute the solutions as well as optimal…

Optimization and Control · Mathematics 2024-12-31 Lander Vanroye , Joris De Schutter , Wilm Decré

Meta-learning has emerged as an important framework for learning new tasks from just a few examples. The success of any meta-learning model depends on (i) its fast adaptation to new tasks, as well as (ii) having a shared representation…

Machine Learning · Computer Science 2019-10-21 Daniel Jiwoong Im , Yibo Jiang , Nakul Verma

Learning-based control methods utilize run-time data from the underlying process to improve the controller performance under model mismatch and unmodeled disturbances. This is beneficial for optimizing industrial processes, where the…

Systems and Control · Electrical Eng. & Systems 2021-11-22 Efe C. Balta , Kira Barton , Dawn M. Tilbury , Alisa Rupenyan , John Lygeros

Differential equations arise in mathematics, physics,medicine, pharmacology, communications, image processing and animation, etc. An Ordinary Differential Equation (ODE) is a differential equation if it involves derivatives with respect to…

Mathematical Software · Computer Science 2015-12-31 A. O. Anidu , S. A. Arekete , A. O. Adedayo , A. O. Adekoya

Solving Linear Ordinary Differential Equations (ODEs) plays an important role in many applications. There are various numerical methods and solvers to obtain approximate solutions. However, few work about global error estimation can be…

Numerical Analysis · Mathematics 2018-04-11 Wenyuan Wu , Wenqiang Yang

We present a method of concatenated quantum error correction in which improved classical processing is used with existing quantum codes and fault-tolerant circuits to more reliably correct errors. Rather than correcting each level of a…

Quantum Physics · Physics 2012-10-26 Zachary W. E. Evans , Ashley M. Stephens

We consider Tikhonov regularization of control-constrained optimal control problems. We present new a-priori estimates for the regularization error assuming measure and source-measure conditions. In the special case of bang-bang solutions,…

Optimization and Control · Mathematics 2017-12-08 Nikolaus von Daniels

In this paper, we present an error analysis of one-stage explicit extended Runge--Kutta--Nystr\"{o}m integrators for semilinear wave equations. These equations are analysed by using spatial semidiscretizations with periodic boundary…

Numerical Analysis · Mathematics 2018-09-18 Bin Wang , Xinyuan Wu

A class of explicit pseudo two-step Runge-Kutta-Nystr\"{o}m (GEPTRKN) methods for solving second-order initial value problems $y'' = f(t,y,y')$, $y(t_0) = y_0$, $y'(t_0)=y'_0$ has been studied. This new class of methods can be considered a…

Numerical Analysis · Mathematics 2022-07-19 Nguyen S. Hoang
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